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If WiFi can find you — instead of you trying to locate a signal for it — the result could be smarter homes, more efficient businesses, and password-free WiFi. According to researchers at MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL), it could also make drones safer by helping them avoid specific locations (including their operators) accurately, or help find lost devices with uber-accurate tracking. It could even enable you to find friends and family members in, for example, a train station or museum in countries where WiFi is not as prevalent as in the U.S., without the need to connect to a WiFi infrastructure.
Developed by a team led by Professor Dina Katabi, the new “wireless localization” technology, called Chronos, operates somewhat like sonar and radar, but with far greater precision. It locates users by calculating the time that it takes for data to travel from one device to another (for example, a cell phone and a wireless router).
Current systems, such as GPS, are generally accurate within a few meters, but Chronos can pinpoint locations within a few centimeters. The researchers say the system is 20 times more accurate than existing systems, computing “time-of-flight” with an average error rate of 0.47 nanoseconds. And unlike GPS, which does not work if you are indoors or underground, Chronos can work anywhere a router is functioning.
Until now, localization systems have required four or five WiFi routers or access points. Determining someone’s position involved triangulating the location from multiple angles. Chronos has the ability to calculate not just the angle but also the distance between a user and an access point, which “allows you to compute the user’s position using just one access point,” says Deepak Vasisht, a doctoral student and lead author on a recently published paper. “This is encouraging news for the many small businesses and consumers that don’t have the luxury of owning several access points.”
However, it’s also a positive development for businesses that already have extensive WiFi networks, Vasisht recently told attendees at the USENIX Symposium on Networked Systems Design and Implementation (NSDI ‘16). Starbucks, for example, is well known for having WiFi inside its coffee shops. “But if you talk to them, they tell us that they’re very much interested in restricting free Wi-Fi access only to their customers. They don’t want to be giving free Wi-Fi to their neighbors, and end up causing congestion for their own customers.” (It’s a common problem: According to the Wi-Fi Alliance, about 32% of respondents to a national survey admitted to using unencrypted WiFi signals.)
Securing networks with passwords can be a nuisance for both customers who connect to them and business owners, who must constantly change the passwords to prevent intruders. Establishing a single access point solves the problem because it automatically authenticates legitimate users based on their location. When the MIT researchers tested Chronos in a cafe, the system was 97% accurate in distinguishing in-store customers from people outside the café.
The researchers anticipate that the technology will have important applications in other contexts, including residential and commercial buildings. In a two-bedroom apartment, for example, Chronos can correctly identify the location an occupant 94% of the time. They believe the technology can play an important role in home automation, or “smart homes,” where multiple systems are connected through the Internet of Things. Knowing who is in the house will assist in personalizing systems such as temperature and lighting levels based on user preferences.
“Imagine having a system like this at home that can continuously adapt the heating and cooling depending on the number of people in the home and where they are,” says Katabi. “Eliminating the need for cooperation between WiFi routers opens up many exciting new applications for localization.”
The success of the Chronos’ tests by researchers suggests that WiFi-based positioning could help in other situations where sensors are either limited or inaccessible. Theoretically, the technology could be used to tag the positions of individuals, for example soccer team players on a field. Its navigational capabilities could also be used in robots for entertainment, military, or commercial purposes. There are myriad possibilities waiting to be developed.